Greater than the parts: a review of the information decomposition approach to causal emergence

Author:

Mediano Pedro A. M.12,Rosas Fernando E.345ORCID,Luppi Andrea I.6789ORCID,Jensen Henrik J.51011ORCID,Seth Anil K.1213ORCID,Barrett Adam B.1214,Carhart-Harris Robin L.315,Bor Daniel12

Affiliation:

1. Department of Psychology, University of Cambridge, Cambridge, UK

2. Department of Psychology, Queen Mary University of London, London, UK

3. Centre for Psychedelic Research, Imperial College London, London, UK

4. Data Science Institute, Imperial College London, London, UK

5. Centre for Complexity Science, Imperial College London, London, UK

6. University Division of Anaesthesia, University of Cambridge, Cambridge, UK

7. Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK

8. Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, UK

9. The Alan Turing Institute, London, UK

10. Department of Mathematics, Imperial College London, London, UK

11. Institute of Innovative Research, Tokyo Institute of Technology Tokyo, Japan

12. Sackler Centre for Consciousness Science, University of Sussex, Brighton, UK

13. CIFAR Program on Brain, Mind, and Consciousness, Toronto, Canada

14. The Data Intensive Science Centre, Department of Informatics, University of Sussex, Brighton, UK

15. Psychedelics Division, Neuroscape, Department of Neurology, University of California, San Francisco, CA, USA

Abstract

Emergence is a profound subject that straddles many scientific disciplines, including the formation of galaxies and how consciousness arises from the collective activity of neurons. Despite the broad interest that exists on this concept, the study of emergence has suffered from a lack of formalisms that could be used to guide discussions and advance theories. Here, we summarize, elaborate on, and extend a recent formal theory of causal emergence based on information decomposition, which is quantifiable and amenable to empirical testing. This theory relates emergence with information about a system’s temporal evolution that cannot be obtained from the parts of the system separately. This article provides an accessible but rigorous introduction to the framework, discussing the merits of the approach in various scenarios of interest. We also discuss several interpretation issues and potential misunderstandings, while highlighting the distinctive benefits of this formalism. This article is part of the theme issue ‘Emergent phenomena in complex physical and socio-technical systems: from cells to societies’.

Funder

Gates Cambridge Trust

Ad Astra Chandria foundation

Wellcome Trust

Publisher

The Royal Society

Subject

General Physics and Astronomy,General Engineering,General Mathematics

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